Here is the picture a lot of business leaders are quietly sitting with: AI tools are being rolled out, budgets are being approved, and the technology is technically working. But no one on the leadership team feels confident about what happens next.

A new research report from ManpowerGroup Talent Solutions, published July 22, 2026, puts a number on that feeling. The study found that only 3% of organizations say their leaders are fully prepared to manage AI-enabled ways of working. Meanwhile, 78% report that employees are already concerned about how AI will affect their jobs.

That gap is the real AI problem most organisations are not talking about.

What the Research Found

The report, “The New Talent Equation: Activating Workforce Confidence at Scale,” was developed with Everest Group and draws on surveys of 80 C-suite executives, CHROs, and senior talent leaders across the US and UK in healthcare, life sciences, manufacturing, and technology.

The headline finding is striking but it gets worse when you look at how deep the unreadiness goes:

• Only 17% of organisations report advanced or transformational workforce readiness, where AI capability is genuinely embedded in workflows and tied to measurable business outcomes.
• 63% of employees report experiencing burnout, driven primarily by stress and heavy workloads.
• 64% of workers say they plan to stay with their current employer, not out of loyalty, but because uncertainty is pushing them toward stability. ManpowerGroup calls this “job hugging.”
• Half of all workers supplement their primary income, rising to 68% among Gen Z.

The researchers are direct about what this means: the biggest obstacle to AI transformation is no longer the technology. It is leadership capability and workforce confidence.

The Leadership Bottleneck

When AI investments stall or fail to produce returns, the instinct is usually to blame the tool, the data, or the implementation partner. This research points somewhere else.

Leaders who have not developed the skills or the vocabulary to coach teams through AI-driven change are creating a vacuum. Employees read that vacuum as danger. They disengage, they hunker down, and the productivity gains that justified the AI spend never materialise.

The problem compounds because AI is moving so fast that traditional training cycles are not catching up. By the time a leadership development program is scoped, approved, and delivered, the tools it was designed around have already changed.

This is not a technology problem. It is a human systems problem.

What This Means for Business

For any organisation that has been pouring money into AI tools and waiting for the results to show up, this research offers a useful re-framing.

The investment was probably not wrong. The sequencing may have been. Getting AI to produce value requires leaders who can translate what the technology makes possible into clear direction for their teams, and workers who feel confident enough to actually use it.

A few practical implications from the data:

Invest in AI leadership capability before adding more AI tools. Adding a new agent platform to a team whose manager does not understand how to supervise AI-assisted work will not accelerate anything.

Data literacy is not just for data teams. When leaders understand how AI systems work at a conceptual level, they make better decisions about where to deploy them and how to interpret what they produce.

Worker confidence is a performance variable. The burnout and stability-seeking described in this research are not passive background conditions. They actively limit how much an organisation can change.

The Bigger Picture

This research lands at a moment when enterprise AI investment is running far ahead of organisational readiness. Gartner recently estimated that 40% of enterprise applications will have embedded AI agents by end of 2026, up from under 5% in 2025. But the tools shipping into those organisations are only as useful as the people deploying them.

The companies that get ahead in this environment will not necessarily be the ones with the biggest AI budgets. They will be the ones that took leadership readiness seriously before the technology arrived, not after it started underperforming.

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Enterprise DNA works with organisations and individuals navigating exactly this transition. For teams building the data and AI literacy that leadership needs, EDNA Learn offers structured training in Power BI, Python, SQL, and AI fundamentals. For business leaders who want a practical AI strategy rather than another tool deployment, Omni Advisory offers fractional guidance from people who have actually built AI-powered operations.